Research-analyst AI on MNPI —
designed against leakage, without lock-in
Investment research, restricted-list cross-checks, earnings-call summaries, peer-comp pulls — every workflow that would amplify your analysts touches material non-public information. The SEC, your CCO, and your prime broker all care about MNPI handling. VeilEngine’s finserv pack lets the workflows run with the audit trail regulators expect.
Your research team wants frontier AI on the deal pipeline — your CCO sees the leakage risk
A research analyst preparing a desk note touches: the restricted list, the live deal book, the earnings transcript pre-publication, the prime-broker exposure, and the firm’s position. Routing any of these to an unprotected LLM provider creates a textbook SEC Reg S-P safeguarding failure and gives FINRA an obvious 17a-4 books-and-records concern. So the workflow doesn’t run, and analysts paste fragments into chat interfaces — which is worse, just unobservable.
Issuer names are protected before the provider — with signed receipts designed for a 17a-4(f) audit trail
VeilEngine’s finserv vertical pack is designed to secure issuer identifiers, deal codes, and MNPI markers at the protection boundary. Restricted-list cross-checks run before any request leaves the firm. Signed per-request receipts are designed to compose into a 17a-4(f)-style audit-trail-alternative record and integrate with your firm’s WORM retention program (engagement-scoped). Provider routing respects per-jurisdiction DPA / data-residency obligations.
- Restricted-list enforcement at the boundary — designed so the LLM does not see a restricted issuer name in the same context as the deal hypothesis
- Designed for 17a-4(f) ERS / audit-trail requirements — signed per-request receipts and a per-session hash-linked chain as supporting books-and-records artifacts, subject to firm policy and counsel review (cross-session transparency-log inclusion proofs are on the roadmap)
- Prime-broker exposure measurable — receipts attest to zero MNPI in provider payload, not assumed
- Provider routing tunes cost — high-volume earnings-call summarization routes to GPT; thesis-stage analysis routes to Claude
Workflows your CCO and head of research sign off on together
Research-note thesis draft
Multi-source analyst draft on restricted-list candidates. Tier 1. ~30s TUA vs. ~3 days through compliance approval (illustrative).
Earnings-call summarization
Real-time earnings transcript summarization with peer-comp context. High-volume; routed to GPT for cost.
Peer-comp pulls
Quantitative + qualitative peer-comp analysis with protected issuer references. Tier 1.
Restricted-list cross-check
Pre-publication check that draft references and references-of-references clear the restricted list. Tier 1 gateway by default; Tier 0 client-side scoped per engagement for highest-sensitivity desks.
Client-suitability narrative
Reg BI / suitability documentation drafted from client profile + product disclosures. Tier 1.
Custom workflow
Bring the specific MNPI-adjacent workflow your CCO has blocked. We scope it during the regulatory audit.
Financial-services AI governance, answered
Bring the desk note your CCO has blocked
We start with a discovery regulatory audit alongside your CCO and head of research. You receive a preliminary exposure map and a 17a-4 audit-trail plan as the diagnostic deliverable — yours to keep regardless of next steps.